Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

A taxonomy characterizing complexity of consumer eHealth Literacy.

Authors: Connie V. Chan; Lisa A. Matthews; David R. Kaufman;

A taxonomy characterizing complexity of consumer eHealth Literacy.

Abstract

There are a range of barriers precluding patients from fully engaging in and benefiting from the spectrum of eHealth interventions developed to support patient access to health information, disease self-management efforts, and patient-provider communication. Consumers with low eHealth literacy skills often stand to gain the greatest benefit from the use of eHealth tools. eHealth skills are comprised of reading/writing/numeracy skills, health literacy, computer literacy, information literacy, media literacy, and scientific literacy [1]. We aim to develop an approach to characterize dimensions of complexity and to reveal knowledge and skill-related barriers to eHealth engagement. We use Bloom's Taxonomy to guide development of an eHealth literacy taxonomy that categorizes and describes each type of literacy by complexity level. Illustrative examples demonstrate the utility of the taxonomy in characterizing dimensions of complexity of eHealth skills used and associated with each step in completing an eHealth task.

Related Organizations
Keywords

Consumer Health Information, Humans, Information Literacy, Computer Literacy, Classification

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Top 10%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!